I review recent advances in nonequilibrium thermodynamics of biochemical networks, organized around two central questions. First, why is free energy dissipation essential for enabling or enhancing biological function? Second, how do energetic costs constrain functional performance? Using several representative systems—beginning with the classical kinetic proofreading mechanism and extending to more recent examples such as accurate sensory adaptation, ultrasensitive responses, and synchronization of biochemical oscillators—I show that this framework not only provides new insights into the molecular mechanisms underlying these diverse processes but also reveals the general thermodynamic principles that govern their biological functions. I highlight the characteristic signatures of nonequilibrium behavior and the emergence of fundamental energy–performance trade-offs. This review strives to present the framework pedagogically and with sufficient technical detail to enable theory-inclined biophysicists to apply it to their own systems of interest. I conclude by proposing a nonequilibrium thermodynamic law for living systems and outlining promising directions for extending this theoretical approach to an even broader range of biological phenomena.
Since the beginning of this century, the emergence of systems biology, driven by technological, informatic, and theoretical advances, has led to an unprecedented generation of data and information about biological systems at multiple levels of organization. We now have access not only to components of living systems but also to some of the underlying principles governing their organization within networks. This review focuses on the systems biology of aging, metabolism, and mitochondria, along with the integration of experimental and computational systems biology approaches as applied to multilayered biological networks, spanning from the molecular-subcellular to the whole organism. Sections 2 and 3 provide an overview of the insights gained from systems biology and multi-omics approaches as applied to aging and metabolism. Using the spatiotemporal dynamics of biological networks as a unifying thread, Sections 4 and 5 explore how systems biology and current methods can leverage the understanding of complex biological phenomena through integrated experimental-computational strategies, utilizing iterative, verification-validation loops between experiments and models. Section 6 concludes by highlighting the autonomously dynamic, self-organizing, and self-regulating integrative nature of living systems and the need to address these properties at the emerging convergence of biology, medicine, physics, and powerful computational technologies that include artificial intelligence.
Photosynthesis, the biological process of converting light energy into chemical energy, involves light harvesting, charge separation and electron transport, proton translocation, ATP synthesis, and carbon fixation, among other processes. Adjacent photosynthetic complexes may assemble into supramolecular complexes to couple and regulate their functions. Here, we review the progress of structural biology studies of photosynthetic supramolecular complexes, such as those that have light-harvesting complexes assembled with photosystem II (PSII) or photosystem I (PSI), both PSII and PSI, or bacterial reaction center complexes. The intricate architectures of the NADH dehydrogenase-like (NDH) complex and PSI-NDH supercomplex, revealed through cryo-electron microscopy studies, provide crucial frameworks for understanding the molecular mechanisms of cyclic electron flow in cyanobacteria and plants. Furthermore, structural studies have also yielded detailed insights into the assembly and repair of PSII, regulation of ATP synthase, and carbon fixation. The review concludes with a summary of the emerging directions of structural biology studies of photosynthetic supramolecular complexes.
Voltage-dependent anion channels (VDACs) of the outer mitochondrial membrane carry out bidirectional flux of metabolites and ions and serve as the first line of communication between the cytosol and mitochondria. They are now recognized as indispensable for mitochondrial function and cellular homeostasis, mitochondria-endoplasmic reticulum communication, lipid and cholesterol biogenesis, Ca2+ homeostasis, and mitochondria-mediated apoptosis. The unique structural features of VDACs are also important in redox regulation. VDAC dysregulation by interaction with amyloid-β, α-synuclein, Tau, or tubulin can lead to neurodegeneration. Here, we provide insights into the structures, isoform-specific molecular functions, cellular interactome, variations, and unique regulatory elements of VDACs and their direct implications for widespread burdens like cancer and neurodegeneration in humans. We discuss how deducing isoform-specific structure-function studies of VDACs has the potential for successful development of next-generation diagnostics-guided therapeutics.
Chemical signaling underlies many biological processes, and membrane receptors such as G protein-coupled receptors and ligand-gated ion channels represent two of the most pharmacologically important protein families. Advances in single-molecule fluorescence techniques have transformed our understanding of molecular mechanisms, including protein folding, transcription, and ligand binding. Unlike ensemble measurements, which average over populations and obscure molecular heterogeneity, single-molecule approaches enable direct observation of individual events, revealing rare conformational states and distinguishing between mechanisms that are indistinguishable at the ensemble level. This review highlights how single-molecule fluorescence resonance energy transfer (smFRET) and single-molecule fluorescence ligand binding (smFLiB) provide complementary insights into ligand-dependent receptor activation and allosteric coupling. smFRET offers structural information by tracking conformational transitions, but limited observation times can hinder detection of slow or infrequent events. In contrast, smFLiB allows long-duration monitoring of ligand-receptor interactions throughout the activation pathway, though with less direct information about structural rearrangements. Through selected case studies, we illustrate how these techniques have been applied to dissect the complexity of ligand-receptor interactions with unprecedented resolution. These advances hold promise for guiding the rational design of more selective and effective therapeutics targeting membrane proteins.
I review recent advances in nonequilibrium thermodynamics of biochemical networks, organized around two central questions. First, why is free energy dissipation essential for enabling or enhancing biological function? Second, how do energetic costs constrain functional performance? Using several representative systems-beginning with the classical kinetic proofreading mechanism and extending to more recent examples such as accurate sensory adaptation, ultrasensitive responses, and synchronization of biochemical oscillators-I show that this framework not only provides new insights into the molecular mechanisms underlying these diverse processes but also reveals the general thermodynamic principles that govern their biological functions. I highlight the characteristic signatures of nonequilibrium behavior and the emergence of fundamental energy-performance trade-offs. This review strives to present the framework pedagogically and with sufficient technical detail to enable theory-inclined biophysicists to apply it to their own systems of interest. I conclude by proposing a nonequilibrium thermodynamic law for living systems and outlining promising directions for extending this theoretical approach to an even broader range of biological phenomena.
Nanopores have become transformative tools in single-molecule chemical analysis, enabling detailed interrogation of molecular interactions and reaction dynamics. These advancements have revolutionized the characterization of chemical kinetics and stereospecificity, broadening nanopore applications. This review evaluates the principles of nanopore single-molecule chemistry, highlighting breakthroughs in chemically reactive nanopore construction via site-specific mutagenesis, semisynthetic engineering, and orthogonal modifications. Notably, we highlight the innovative strategies enabling precise subunit stoichiometry control to ensure single-molecule reactions, and the integration of machine learning for high-fidelity ionic current analysis. These developments position nanopores as versatile tools for intricate molecular detection in fundamental and applied research. Looking forward, nanopore single-molecule chemistry promises an impact on diagnostics, environmental monitoring, and precision medicine. Integration of molecular dynamics simulations, artificial intelligence-driven protein design frameworks, and microsystems technology may expand detectable species, enhancing robustness and lowering detection limits. Such advancements will deepen our understanding of chemical transformations and support meaningful real-world applications of nanopore technologies.
Pattern formation, or the emergence of spatial order and fate specification from initially homogeneous cell populations, is a fundamental problem in developmental biology and biophysics. In vitro cell culture platforms now provide powerful tools to investigate the mechanisms of pattern formation under controlled conditions. In this review, we present an integrated perspective on recent advances in pattern formation studies across a diverse array of in vitro systems, organized thematically by the experimental platforms they employ and the underlying principles they reveal, ranging from biochemical gradients to dynamic signaling and mechanochemical feedback. We discuss how these systems recapitulate principles such as morphogen gradients and reaction-diffusion dynamics while enabling mechanistic dissection of self-organization. Particular emphasis is placed on stem cell-based models of early human development that provide unique access to early developmental patterning. We further explore how dynamic signaling, collective behavior, and multisignal integration define emergent patterning phenomena. Finally, we outline future challenges and opportunities in combining theoretical and experimental approaches to model and engineer spatial organization in multicellular systems.
Cells process signals by using large and complex networks of molecules that interact with and modify one another. Some of these interactions occur among molecules connected by long flexible tethers, often made of intrinsically disordered protein regions. In this review, we present recent research showing that tethered reactions (a) are ubiquitous in cells, (b) are exploited by cell signaling networks, (c) can be qualitatively and quantitatively understood using simple polymer physics, (d) give rise to categorically different features compared with molecular interactions driven by free diffusion, and (e) provide novel avenues for therapeutics and bioengineering. Recent studies have begun to shed light on cases in which the tethers must reach between different molecular assemblies that are not connected by protein scaffolding. We provide an in-depth case study of immune receptors, where such tethered signaling plays a vital role in signal integration and immune cell decisions.
The spatiotemporal organization of intracellular compartments is fundamental to cellular function and to the understanding of the processes underpinning health and disease. Fluorescence microscopy offers a powerful means to observe organelle morphology and dynamics with high specificity. However, no single technique can capture the wide range of relevant spatiotemporal scales due to inherent trade-offs in resolution, speed, field of view, signal-to-noise ratio, and sample viability. In this review, we describe recent developments across high-resolution fluorescence microscopy techniques and associated computational methods, critically evaluating how these advances address key limitations. Through biological examples of organelle dynamics at different scales, we illustrate the impact of these technologies on our understanding of cellular organization and function. Finally, we discuss the current challenges and outline future directions for imaging-based research, highlighting the potential for further innovations to deepen insights into dynamic subcellular processes.
Single-molecule techniques have transformed biological research by enabling direct observation and manipulation of individual molecules. These methods overcome ensemble averaging inherent in bulk measurements and facilitate studies under physiological stresses and out-of-equilibrium conditions. They have provided valuable insights into diverse biological processes, from stepping mechanisms of molecular motors to mechanical properties of biomolecules to the dynamic strength of intermolecular bonds. Advances in multiplexed and high-throughput single-molecule force spectroscopy methods are improving throughput, capabilities, and accessibility. In this review, we detail the evolution of multiplexed force spectroscopy technologies, highlighting key advances in instrumentation, molecular engineering, and analytical techniques. We discuss diverse applications spanning molecular biophysics, biomolecular sensing, proteomics, and cellular mechanobiology. Finally, we explore ongoing challenges and future opportunities and highlight how the impact of multiplexed single-molecule force spectroscopy can continue to grow through further developments in novel instrumentation, chemical tools, and innovative applications.
Intracellular protein patterns govern essential cellular functions by dynamically redistributing proteins between membrane-bound and cytosolic states, conserving their total numbers. This review presents a theoretical framework for understanding such patterns based on mass-conserving reaction–diffusion systems. The emergence, selection, and evolution of patterns are analyzed in terms of mass redistribution and interface motion, resulting in mesoscale laws of coarsening and wavelength selection. A geometric phase-space perspective provides a conceptual tool to link local reactive equilibria with global pattern dynamics through conserved mass fluxes. The Min protein system of Escherichia coli provides a paradigmatic example, enabling direct comparison between theory and experiment. Successive model refinements capture both the robustness of pattern formation and the diversity of dynamic regimes observed in vivo and in vitro. The Min system thus illustrates how to extract predictive, multiscale theory from biochemical detail, providing a foundation for understanding pattern formation in more complex and synthetic systems.
T cells are central to the adaptive immune response, capable of detecting pathogenic antigens while ignoring healthy tissues with remarkable specificity and sensitivity. Quantitatively understanding how T cell receptors discern among antigens requires biophysical models and theoretical analyses of signaling networks. Here, we review current theoretical frameworks of antigen recognition in the context of modern experimental and computational advances. Antigen potency spans a continuum and exhibits nonlinear effects within complex mixtures, challenging discrete classification and simple threshold-based models. This complexity motivates the development of models, such as adaptive kinetic proofreading, that integrate both activating and inhibitory signals. Advances in high-throughput technologies now generate large-scale, quantitative data sets, enabling the refinement of such models through statistical and machine learning approaches. This convergence of theory, data, and computation promises deeper insights into immune decision-making and opens new avenues for rational immunotherapy design.
Rigidity is an emergent property of materials-it is not a feature of individual components that compose the structure, but instead arises from interactions between many constituent parts. It has been recognized that floppy-rigid or fluid-solid transitions are harnessed by biological systems at all scales to drive form and function. This review focuses on the different mechanisms that can drive emergent rigidity transitions in biomechanical networks and describes how they arise in mathematical formalisms and how they are observed in practice in experiments. The goal is to aid researchers in identifying mechanisms governing rigidity in their biological systems of interest, highlight mechanical features that are universal across different systems, and help drive new scientific hypotheses for observed mechanical phenomena in biology. Looking forward, we also discuss how biological systems might tune themselves toward or away from such transitions over developmental or evolutionary timescales.
Hopfield models, originally developed to study memory retrieval in neural networks, have become versatile tools for modeling diverse biological systems in which function emerges from collective dynamics. In this review, we provide a pedagogical introduction to both classical and modern Hopfield networks from a biophysical perspective. After presenting the underlying mathematics, we build physical intuition through three complementary interpretations of Hopfield dynamics: as noise discrimination, as a geometric construction defining a natural coordinate system in pattern space, and as gradient-like descent on an energy landscape. We then survey recent applications of Hopfield networks a variety of biological setting including cellular differentiation and epigenetic memory, molecular self-assembly, and spatial neural representations.
Over the last decade, proteomic analysis of single cells by mass spectrometry transitioned from an uncertain possibility to a set of robust and rapidly advancing technologies supporting the accurate quantification of thousands of proteins. We review the major drivers of this progress, from establishing feasibility to powerful and increasingly scalable methods. We focus on the tradeoffs and synergies of different technological solutions within a coherent conceptual framework, which projects considerable room both for throughput scaling and for extending the analysis scope to functional protein measurements. We highlight the potential of these technologies to support the development of mechanistic biophysical models and help uncover new principles.
Bacteria are unicellular organisms that typically lack membrane-bound organelles. Nevertheless, they are not merely "bags of enzymes" and instead use alternate mechanisms to organize their components in space and time. Biomolecular condensates are a newly described class of membraneless compartment that organizes cellular functions in bacteria. In this review, we cover key biophysical features of bacterial cells and discuss how their finite size and crowded interior may affect condensate nucleation and stability. Next, we describe three examples of endogenous condensates, highlighting the molecular components driving their formation and the functional roles they may play in cells. Finally, we provide an overview of current and prospective tools to study and manipulate both endogenous and synthetic condensates alike. Overall, bacterial condensates present a fascinating system to explore open questions that span the disciplines of biophysics, molecular and cell biology, and bioengineering.
The mitochondrial permeability transition (PT) is a Ca2+-dependent permeability increase of the inner mitochondrial membrane mediated by opening of a high-conductance channel, the PT pore. Its molecular nature has been the subject of intense research and the source of controversies, but a considerable consensus has been reached that the PT originates from specific conformations of the FOF1-ATP synthase and of the adenine nucleotide translocator. The ATP synthase forms high-conductance channels in mammals and yeast but not in the anoxia- and salt-tolerant brine shrimp Artemia franciscana, which is refractory to the PT; it forms low-conductance and Ca2+-selective channels in Drosophila melanogaster, which undergoes a process of Ca2+-induced Ca2+ release but not a PT. The structural definition of ATP synthases from several species may allow for some inferences to be made about the mechanism of channel formation, or lack thereof, and provides a testable framework for future research.
Histones are small basic proteins that form the proteinaceous core of the nucleosome, the repeating building block of chromatin in all eukaryotes. Long thought to be exclusive to eukaryotes, histones are now increasingly appreciated for their roles in organizing genomes across all domains of life, namely in archaea, bacteria, and even viruses. We survey recent advances in our understanding of the imaginative uses of histones in disparate biological entities, ranging from nucleosome-like metastable particles in giant viruses to slinky-like hypernucleosomes in archaea to bacterial histones that bind DNA in decidedly unorthodox ways. Across these different contexts, we examine how DNA compaction and conformation emanate from evolutionarily conserved aspects of histone structure, including how the oligomeric states of histones dictate their capacity to contort DNA in different conformations. It appears that relatively small tweaks to the amino acid sequences of histones can result in structural and functional variations in DNA binding. As such, nucleosomes in eukaryotes sample only a narrow range of possible structures.
While the role of water in soluble protein structure and function is well-established, the analogous role of lipids as a solvent for membrane proteins is less understood. Bacterial membranes exhibit extraordinary lipid diversity, with Escherichia coli synthesizing over 1,800 distinct glycerophospholipids. This lipid diversity gives rise to bulk membrane properties and specific lipid–lipid and lipid–protein interactions that directly affect α-IMP folding, assembly, and function. In this review, we use the same thermodynamic framework for understanding the solvation of soluble proteins to examine bacterial α-helical integral membrane protein (α-IMP) interactions with chemically diverse lipid environments. We propose that preferential solvent interactions were essential evolutionary drivers that enabled lipids to evolve as protein cofactors and substrates, with lipid chemical diversity creating unique evolutionary pressures distinct from those of aqueous systems.
